extremes seminar: tornadoesamfiore/eescg9910_f14_ppts/annan.pdffrancis annan extremes seminar:...

IntroductionPaper 1Paper 2Paper 3

Extremes Seminar: Tornadoes

Francis Annan

Dec. 01, 2014

Francis Annan Extremes Seminar: Tornadoes


Outline

1 Introduction

2 Paper 1

3 Paper 2

4 Paper 3



Introduction

101: What is a tornado? According to the Glossary of Meteorology (AMS 2000), atornado is ”a violently rotating column of air, pendant from a cumuliform cloud orunderneath a cumuliform cloud, and often (but not always) visible as a funnel cloud.”



3-Papers:

1 Does Global Warming Influence Tornado Activity? (by N.Diffenbaugh, R. Trapp and H. Brooks 2008)

2 Severe thunderstorms and climate change. (by H. Brooks2012)

3 Robust increases in severe thunderstorm environments inresponse to greenhouse forcing. (by N. Diffenbaugh, M.Scherer and R. Trapp)



Paper 1

Main question: does global warming influence Tornadoactivity?

Tornadoes (+other severe thunderstorms) frequently cause asmuch annual property damage in the U.S. as do hurricanes

In fact, often cause more fatalities

In 2008: there were 2176 preliminary tornado reports loggedthrough mid-December, with 1600 “actual counts” (duplicatereports removed) through September

This is the highest total in the past half century (Figure 1)



These may be potentially linked to anthropogenic globalwarming

Recent research has yielded insight into the connectionsbetween global warming and tornado and severe thunderstormforcing

But these relationships remain mostly unexplored: largelybecause of the challenges in observing and numericallysimulating tornadoes

Paper explores the challenges and opportunities in pursuingpossible research areas (trends and causes of Tornadooccurrence)



Tornado Trend Detection

The number of tornadoes reported in the United States peryear has been increasing steadily (˜14 per year) over the pasthalf century (below: Figure 2)



Difficulties in Tornado trend detection:

1 short historical record, ≥1950s

2 nonuniform in space and time redords

3 observational record based on a reporting system designedessentially for the verification of forecasts rather than forresearch-quality climate studies

4 reliance on human reports leaves trends subject to externalinfluences (e.g. population growth)

although some regions such as the southern Great Plains donot reflect the congruous long-term trends in tornadooccurrence and population growth comapred to the entireU.S. (Figure 2)



The number of tornadoes classified as the most damaging(rated F2–F5 on Fujita scale) appears to have decreased overthe period (Figure 2)?

Generally, Tornado trend detection is complex: may requireappropriate statistical models and developement of otheranalysis approaches(e.g. coupling climatological informationwith tornado-report proxies)



Tornado Trend Attribution: a review

Changes in seasonal tornado activity can plausibly beexplained by shifts in the mean jet stream position associatedwith the ENSO (e.g. see Cook and Schaefer 2008)

Yet the literature does not provide clear consensus about thenature of links between tornadoes and “natural” climatevariability

Also global warming could affect the frequency, seasonality,and spatial distribution of severe thunderstorms and tornadoes



Severe thunderstorms that spawn tornadoes arise inlarger-scale environments characterized by large vertical WindShear and Convective Available Potential Energy (CAPE)

More generally, global warming is expected to increase CAPEby increasing temperature and humidity within theatmospheric boundary layer while simultaneously weakeningvertical wind shear by decreasing the pole-to- equatortemperature gradient (e.g. see Trapp et al. 2007a)



The regions that experience peak tornado occurrence atpresent could therefore see reductions due to weakened smallShear

But the reductions could be offset by increased CAPE, whichcould lead to increased tornado occurrence

Also changes in Shear and CAPE can modify the seasons oftornado forcing: e.g. with enhanced cool-season activity



Warming can potentially shift the regions of greatest tornadooccurrence poleward by shifting peak Shear poleward whilesimultaneously increasing CAPE in those same regions

Generally, Tornado trend attribution is complex: may requirethe consideration of other facets e.g. the effect of globalwarming on the initiation of the deep convective clouds thatbecome tornadic storms

Future Changes in Tornado Activity: limitations in currentknowledge and climate model resolution +uncertainty pose challenges for projecting futurechanges



Paper 2

Examines distribution of severe thunderstorms =f(large-scaleenvironmental conditions /Warming)

Preview of findings:

(i) severe thunderstorms are much more likely to form inenvironments with large values of deep-tropospheric windShear and CAPE

(ii) Tornadoes and hail and their intensities tends to entirelybe a function of the Shear and weakly depends on thethermodynamics

Caveat: Climate model simulations suggest that CAPE will increase and windShear will decrease -> the directions of future Tornadoes and hail changes isopen to question



While global average temperature may be of less importanceto most of society, changes in local weather events(particularly extreme events) are of greater concern

Tropical cyclones(hurricanes) have received significantresearch attention in the last decade, but

Limited research attention on severe thunderstorms(Tornadoes and large hail) and their linkages with globalclimate (1. data/report limitations, and 2. smallhorizontal nature makes it difficult to analyse with largegrid global models)

Therefore: IPCC Assessment Reports on thunderstorms ismarginal; tend to be a paragraph or two



Reports:

Typically “target of opportunity” observations: limited datareport systems; available systems collect information mainlyfor forecasting purposes -> so posses data interpretationproblems with inhomogeneities

Pointed out that: previous studies (e.g. Xie et al. 2008) foundevidence of larger Hail formation in higher CAPE environments

Problems: these are mall pockets of studies; only go back23-25 yrs -> so hard to have confidence in the long termtrends



Environmental-Estimates:

Utilize meteorological covariates approach to circumvent useof reports challenges

Covariates relate environmental conditions (may bewell-observed) to weather events of greater interest (but arenot well-observed)

Pointed out that: previous studies have used reanalysis data(env. conditions) to estimate distribution of severethunderstorms and tornadoes

E.g. Allen et al. (2011) did analysis for Australia and found aroughly parallel discrimination line for dataset, approx.

CAPE ∗ SHR61.6 = k

where k is some constant: -> deep Shear is more important thanCAPE for discriminating between severe and non-severethunderstorms



Examine WMAX-SHR6 space (Gaussian Kernel smoother),where from parcel theory: WMAX =

√2× CAPE

The distribution of sounding values shows that mostthunderstorm soundings occur for combinations/(joint) ofrelatively small WMAX and SHR6 (above: Fig.1)Francis Annan Extremes Seminar: Tornadoes


The distribution in WMAX-SHR6 of significant severethunderstorm soundings shows that they tend to occur off ofthe WMAX or SHR6= 0 axes (below: Fig. 2)



Gaussian Kernel Smoother

The probability of a significant severe thunderstorm showsmuch higher probabilities as the WMAX and SHR6 increase



There are similarities in the distribution for the ESWD data(below Fig. 4)

but: the distribution does not extend to as high of values ofWMAX (≤ 65); conditional probability for severe muchhigher(≥ 4%)



Next, (below: Fig. 5)

Probability of a significant severe thunderstorm producingtornado or hail incr. with incr. in SHR6; probability of windincr. with decr. in SHR6; insignificant for WMAX



Summarize observed relationship using

Clearly, dividing line between greater and lesser probabilitycompared to base rate is almost the same line for all 3 threatsover a broad range of WMAXFrancis Annan Extremes Seminar: Tornadoes


Modelling-Studies:review

Number studies carried out to quantify climate changeimpacts on severe thunderstormsDifferent conclusions or evidence in some parts of the world,e.g. Southern Australiabut, Consistent results found in the U.S.:

1 CAPE (or WMAX) increasing over most of the US east of theRockies: driven by increases in boundary layer moisture assurface temperatures warm

2 SHR6 decreasing over much of the US: driven mainly by areduction in temperature differences(equator-to-pole) andthermal wind changes

Climate model simulations suggest increase in CAPE anddecrease in Shear -> the directions of future Tornadoes andhail changes is open



Paper 3

Motivation: Severe thunderstorms are one of the primary causesof catastrophic loss in the U.S.; yet their response togreenhouse forcing is uncertain for CC impactassessments

Model severe thunderstorms =f(greenhouse forcing)

Preview of findings:

(i) Evidence of robust increases in occurrence of severethunderstorm environments (over eastern U.S.) in response tofurther global warming

(ii) For spring and autumn: these robust increases emergebefore mean global warming of 20C



(iii) Find that days with high CAPE and strong low-level windShear increase in occurrence.

This suggests an incr. chance of atmospheric conditions thattrigger severe events, e.g Tornado

(iv) Find that decreases in Shear are concentrated in dayswith low CAPE and therefore do not decrease the totaloccurrence of severe environments

Evidences are:robust across a sequel of climate models &occur in response to moderate g-warming



Classified modelling approaches into 2: explicit and implicit

Explicit approaches: use horizontal and vertical resolutions thatpermit an explicit representation of deep convective storms andtheir implied characteristics

Con: limited to short integrations of a single model orsimulations of individual events over relatively smallcomputational domains

Implicit approaches: (Covariates?) examine atmosphericenvironments that are known to support severe thunderstormformation in the current climate

Con: arguments around decreasing Shear creates uncertaintyabout the response of severe thunderstorm



Here (use mplicit approach) to analyze severe thunderstormenvironments in Coupled Model Intercomparison Project,Phase 5 (CMIP5) global climate model ensemble

Focus on representative concentration pathway (RCP) 8.5–this covers the full range of 21st century radiative forcingand global warming spanned by the illustrative RCPs

Defined a severe Thunderstorm day=vertical wind Shear(over a 6km layer, S06)× CAPE



Results

Ensemble-mean number of days with severe thunderstormenvironments (NDSEV) increases over the eastern US. in all4-seasons in response to the RCP8.5 forcing pathway (below:Fig. 1)

Winter (DJF) exhibits the largest relative increase in regionalmean NDSEV

Spring (MAM) exhibits the most consistent response acrossthe ensemble, with all models exhibiting positive multidecadalanomalies



Evidence of spatial pattern and seasonal variations of NDSEV

changes: largest and most robust increases in 2070-2099 occur over

central US in spring(Fig B)



The NDSEV changes in 2070–2099 are linked withensemble-mean increases in seasonal CAPE andensemble-mean decreases in seasonal Shear(S06) for all nearlyareas and seasons (below: Fig. 2)



Changes in CAPE and Shear in the different seasons may be explained inpart by changes in the Vertical structure of the atmosphere(Fig. 3)

negligible change in spring(MAM)-season zonal wind below 8 km -> explain lack of robust change in spring S06(Fig. 2F)robust decreases in summer(JJA)-season zonal wind around 6 km -> explain the robust decrease in summer S06(Fig. 2G)robust warming below 300 mb (˜9 km) over the eastern US + robust increases in specific humidity at lowest atmlevels



The influence of changing CAPE and Shear on total # of dayswith severe environments arise from changes in daily-scalecombinations of CAPE and shear (Fig. 4)

Difference in daily-scale CAPE-Shear distribution between the2070-2099 and 1970-1999 periods reveals that dailyCAPE-S06 distribution shifts toward increasing occurrence ofhigh CAPE in spring, summer, and autumn: So

1 The occurrence of days in which NDSEV threshold is metincreases

2 The number and fraction of severe days (SEVs) that exhibithigh CAPE increases



Decreases in S06 are concentrated almost entirely in thelow-CAPE/high-shear portion of the CAPE-S06 distribution

Implication: Since severe environments require sufficient levels of bothCAPE and Shear, loss of high-shear days at very low levels of CAPE hasno effect NDSEV occurrence (see black curves).Therefore NDSEVincreases over the eastern U.S. in all four seasons


extremes seminar: tornadoesamfiore/eescg9910_f14_ppts/annan.pdffrancis annan extremes seminar:...

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